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Exponential mean square stability of numerical methods for systems of stochastic differential equations

机译:随机微分方程系统数值方法的指数均方稳定性

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This paper is concerned with exponential mean square stability of the classical stochastic theta method and the so called split-step theta method for stochastic systems. First, we consider linear autonomous systems. Under a sufficient and necessary condition for exponential mean square stability of the exact solution, it is proved that the two classes of theta methods with θ<0.5 are exponentially mean square stable for all positive step sizes and the methods with θ<0.5 are stable for some small step sizes. Then, we study the stability of the methods for nonlinear non-autonomous systems. Under a coupled condition on the drift and diffusion coefficients, it is proved that the split-step theta method with θ>0.5 still unconditionally preserves the exponential mean square stability of the underlying systems, but the stochastic theta method does not have this property. Finally, we consider stochastic differential equations with jumps. Some similar results are derived.
机译:本文关注经典随机theta方法的指数均方稳定性和随机系统所谓的分步式theta方法。首先,我们考虑线性自治系统。在精确解具有指数均方稳定性的充分必要条件下,证明了θ<0.5的两类θ方法对于所有正步长均是指数均方稳定的,而θ<0.5的方法对于所有正步长都是稳定的。一些小的步长。然后,我们研究了非线性非自治系统方法的稳定性。在漂移和扩散系数耦合的条件下,证明了θ> 0.5的分步θ方法仍然无条件地保持了下层系统的指数均方稳定性,但是随机θ方法没有这种性质。最后,我们考虑带跳的随机微分方程。得出一些类似的结果。

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